Tradememory Protocol

Name: Tradememory Protocol
Author: mnemox-ai

@mnemox-ai

About Tradememory Protocol

Structured 3-layer memory system for AI trading agents. L1 records every trade automatically. L2 discovers patterns via reflection engine. L3 evolves strategy in real-time. Built on MCP. Supports MT5, Binance, Alpaca. Python/FastAPI/SQLite. MIT licensed.

#trading #finance #memory #ai-agent #python #mt5 #forex #algorithmic-trading

Basic information

Config

Add this server to your MCP-compatible client using the configuration below.

{
  "mcpServers": {
    "tradememory": {
      "command": "uvx",
      "args": [
        "tradememory-protocol"
      ]
    }
  }
}

Tools

No tools detected

We auto-extract tools from the README. The maintainer can list them under a ## Tools heading to populate this section.

Overview

What is Tradememory Protocol?

Tradememory Protocol is a structured 3-layer memory system for AI trading agents. It automatically records every trade (L1), discovers patterns via a reflection engine (L2), and evolves strategy in real-time (L3). Built on MCP, it supports MT5, Binance, and Alpaca exchanges. Implemented in Python/FastAPI with SQLite storage. MIT licensed.

How to use Tradememory Protocol?

As an MCP server, Tradememory Protocol is invoked by compatible MCP clients. The implementation uses Python, FastAPI, and SQLite. It supports configuration for MetaTrader 5 (MT5), Binance, and Alpaca exchanges. No specific commands or config keys are documented in the README.

Key features of Tradememory Protocol

3-layer memory for trading agents
L1 records every trade automatically
L2 discovers patterns via reflection engine
L3 evolves strategy in real-time
Supports MT5, Binance, Alpaca exchanges
Built on MCP with Python/FastAPI/SQLite

Use cases of Tradememory Protocol

Automatically record every trade made by an AI trading agent

Comments

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